Awesome-LLM-for-RecSys

A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.

😆 Please check out our survey paper for LLM-enhanced RS: How Can Recommender Systems Benefit from Large Language Models: A Survey

To catch up with the latest research progress, this repository will be actively maintained as well as our released survey paper. Newly added papers will first appear in 1.6 Paper Pending List: to be Added to Our Survey Paper section.

🚀 2023.06.29 - Paper v4 released: 7 papers have been newly added.

Survey Paper Update Logs

2023.06.29 - Paper v4 released: 7 papers have been newly added.
2023.06.28 - Paper v3 released: Fix typos.
2023.06.12 - Paper v2 released: Add summerization table in the appendix.
2023.06.09 - Paper v1 released: Initial version.

1. Papers

We classify papers according to where LLM will be adapted in the pipeline of RS, which is summarized in the figure below.

1.1 LLM for Feature Engineering

Name	Paper	LLM Backbone (Largest)	LLM Tuning Strategy	Publication	Link
GReaT	Language Models are Realistic Tabular Data Generators	GPT2-medium (355M)	Full Finetuning	ICLR 2023	[Link]
GENRE	A First Look at LLM-Powered Generative News Recommendation	ChatGPT	Frozen	Arxiv 2023	[Link]
AnyPredict	AnyPredict: Foundation Model for Tabular Prediction	ChatGPT	Frozen	Arxiv 2023	[Link]
LLM4KGC	Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs	PaLM (540B)/ ChatGPT	Frozen	Arxiv 2023	[Link]
TagGPT	TagGPT: Large Language Models are Zero-shot Multimodal Taggers	ChatGPT	Frozen	Arxiv 2023	[Link]
ICPC	Large Language Models for User Interest Journeys	LaMDA (137B)	Full Finetuning/ Prompt Tuning	Arxiv 2023	[Link]
DPLLM	Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models	T5-XL (3B)	Full Finetuning	Arxiv 2023	[Link]
KAR	Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models	ChatGPT	Frozen	Arxiv 2023	[Link]
MINT	Large Language Model Augmented Narrative Driven Recommendations	GPT3 (175B)	Frozen	RecSys 2023	[Link]

1.2 LLM as Feature Encoder

Name	Paper	LLM Backbone (Largest)	LLM Tuning Strategy	Publication	Link
U-BERT	U-BERT: Pre-training User Representations for Improved Recommendation	BERT-base (110M)	Full Finetuning	AAAI 2021	[Link]
UNBERT	UNBERT: User-News Matching BERT for News Recommendation	BERT-base (110M)	Full Finetuning	IJCAI 2021	[Link]
PLM-NR	Empowering News Recommendation with Pre-trained Language Models	RoBERTa-base (125M)	Full Finetuning	SIGIR 2021	[Link]
Pyramid-ERNIE	Pre-trained Language Model based Ranking in Baidu Search	ERNIE (110M)	Full Finetuning	KDD 2021	[Link]
ERNIE-RS	Pre-trained Language Model for Web-scale Retrieval in Baidu Search	ERNIE (110M)	Full Finetuning	KDD 2021	[Link]
CTR-BERT	CTR-BERT: Cost-effective knowledge distillation for billion-parameter teacher models	Customized BERT (1.5B)	Full Finetuning	ENLSP 2021	[Link]
ZESRec	Zero-Shot Recommender Systems	BERT-base (110M)	Frozen	Arxiv 2021	[Link]
UniSRec	Towards Universal Sequence Representation Learning for Recommender Systems	BERT-base (110M)	Frozen	KDD 2022	[Link]
PREC	Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation	BERT-base (110M)	Full Finetuning	COLING 2022	[Link]
MM-Rec	MM-Rec: Visiolinguistic Model Empowered Multimodal News Recommendation	BERT-base (110M)	Full Finetuning	SIGIR 2022	[Link]
Tiny-NewsRec	Tiny-NewsRec: Effective and Efficient PLM-based News Recommendation	UniLMv2-base (110M)	Full Finetuning	EMNLP 2022	[Link]
PLM4Tag	PTM4Tag: Sharpening Tag Recommendation of Stack Overflow Posts with Pre-trained Models	CodeBERT (125M)	Full Finetuning	ICPC 2022	[Link]
TwHIN-BERT	TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations	BERT-base (110M)	Full Finetuning	Arxiv 2022	[Link]
TransRec	TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback	BERT-base (110M)	Full Finetuning	Arxiv 2022	[Link]
VQ-Rec	Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders	BERT-base (110M)	Frozen	WWW 2023	[Link]
IDRec vs MoRec	Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited	BERT-base (110M)	Full Finetuning	SIGIR 2023	[Link]
TransRec	Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights	RoBERTa-base (125M)	Layerwise Adapter Tuning	Arxiv 2023	[Link]
LSH	Improving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative Study	BERT-base (110M)	Full Finetuning	Arxiv 2023	[Link]
TCF	Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights	OPT-175B (175B)	Frozen/ Full Finetuning	Arxiv 2023	[Link]

1.3 LLM as Scoring/Ranking Function

1.3.1 Item Scoring Task

Name	Paper	LLM Backbone (Largest)	LLM Tuning Strategy	Publication	Link
LMRecSys	Language Models as Recommender Systems: Evaluations and Limitations	GPT2-XL (1.5B)	Full Finetuning	ICBINB 2021	[Link]
PTab	PTab: Using the Pre-trained Language Model for Modeling Tabular Data	BERT-base (110M)	Full Finetuning	Arxiv 2022	[Link]
UniTRec	UniTRec: A Unified Text-to-Text Transformer and Joint Contrastive Learning Framework for Text-based Recommendation	BART (406M)	Full Finetuning	ACL 2023	[Link]
Prompt4NR	Prompt Learning for News Recommendation	BERT-base (110M)	Full Finetuning	SIGIR 2023	[Link]
RecFormer	Text Is All You Need: Learning Language Representations for Sequential Recommendation	LongFormer (149M)	Full Finetuning	KDD 2023	[Link]
TabLLM	TabLLM: Few-shot Classification of Tabular Data with Large Language Models	T0 (11B)	Few-shot Parameter-effiecnt Finetuning	AISTATS 2023	[Link]
Zero-shot GPT	Zero-Shot Recommendation as Language Modeling	GPT2-medium (355M)	Frozen	Arxiv 2023	[Link]
FLAN-T5	Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction	FLAN-5-XXL (11B)	Full Finetuning	Arxiv 2023	[Link]
BookGPT	BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model	ChatGPT	Frozen	Arxiv 2023	[Link]
TALLRec	TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation	LLaMA (7B)	LoRA	RecSys 2023	[Link]
PBNR	PBNR: Prompt-based News Recommender System	T5-small (60M)	Full Finetuning	Arxiv 2023	[Link]

1.3.2 Item Generation Task

Name	Paper	LLM Backbone (Largest)	LLM Tuning Strategy	Publication	Link
GPT4Rec	GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation	GPT2 (110M)	Full Finetuning	Arxiv 2023	[Link]
UP5	UP5: Unbiased Foundation Model for Fairness-aware Recommendation	T5-base (223M)	Full Finetuning	Arxiv 2023	[Link]
VIP5	VIP5: Towards Multimodal Foundation Models for Recommendation	T5-base (223M)	Layerwise Adater Tuning	Arxiv 2023	[Link]
P5-ID	How to Index Item IDs for Recommendation Foundation Models	T5-small (61M)	Full Finetuning	Arxiv 2023	[Link]
FaiRLLM	Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation	ChatGPT	Frozen	RecSys 2023	[Link]
PALR	PALR: Personalization Aware LLMs for Recommendation	LLaMA (7B)	Full Finetuning	Arxiv 2023	[Link]
ChatGPT	Large Language Models are Zero-Shot Rankers for Recommender Systems	ChatGPT	Frozen	Arxiv 2023	[Link]
AGR	Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT	ChatGPT	Frozen	Arxiv 2023	[Link]
NIR	Zero-Shot Next-Item Recommendation using Large Pretrained Language Models	GPT3 (175B)	Frozen	Arxiv 2023	[Link]
GPTRec	Generative Sequential Recommendation with GPTRec	GPT2-medium (355M)	Full Finetuning	Gen-IR@SIGIR 2023	[Link]
ChatNews	A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News	ChatGPT	Frozen	Arxiv 2023	[Link]

1.3.3 Hybrid Task

Name	Paper	LLM Backbone (Largest)	LLM Tuning Strategy	Publication	Link
P5	Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)	T5-base (223M)	Full Finetuning	RecSys 2022	[Link]
M6-Rec	M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems	M6-base (300M)	Option Tuning	Arxiv 2022	[Link]
InstructRec	Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach	FLAN-T5-XL (3B)	Full Finetuning	Arxiv 2023	[Link]
ChatGPT	Is ChatGPT a Good Recommender? A Preliminary Study	ChatGPT	Frozen	Arxiv 2023	[Link]
ChatGPT	Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent	ChatGPT	Frozen	Arxiv 2023	[Link]
ChatGPT	Uncovering ChatGPT's Capabilities in Recommender Systems	ChatGPT	Frozen	RecSys 2023	[Link]

1.4 LLM for RS Pipeline Controller

Name	Paper	LLM Backbone (Largest)	LLM Tuning Strategy	Publication	Link
Chat-REC	Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System	ChatGPT	Frozen	Arxiv 2023	[Link]
RecLLM	Leveraging Large Language Models in Conversational Recommender Systems	LLaMA (7B)	Full Finetuning	Arxiv 2023	[Link]

1.5 Other Related Papers

1.5.1 Related Survey Papers

Paper	Publication	Link
Large Language Models for Generative Recommendation: A Survey and Visionary Discussions	Arxiv 2023	[Link]
Large Language Models for Information Retrieval: A Survey	Arxiv 2023	[Link]
When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities	Arxiv 2023	[Link]
Recommender Systems in the Era of Large Language Models (LLMs)	Arxiv 2023	[Link]
A Survey on Large Language Models for Recommendation	Arxiv 2023	[Link]
Pre-train, Prompt and Recommendation: A Comprehensive Survey of Language Modelling Paradigm Adaptations in Recommender Systems	Arxiv 2023	[Link]
Self-Supervised Learning for Recommender Systems: A Survey	Arxiv 2022	[Link]

1.5.2 Other Papers

Paper	Publication	Link
Evaluation of Synthetic Datasets for Conversational Recommender Systems	Arxiv 2023	[Link]
Generative Recommendation: Towards Next-generation Recommender Paradigm	Arxiv 2023	[Link]
Towards Personalized Prompt-Model Retrieval for Generative Recommendation	Arxiv 2023	[Link]
Generative Next-Basket Recommendation	RecSys 2023	[Link]

1.6 Paper Pending List: to be Added to Our Survey Paper

Name	Paper	LLM Backbone (Largest)	LLM Tuning Strategy	Publication	Link
	Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences			RecSys 2023	[Link]
	LLM4Rec: Large Language Models for Recommendation via A Lightweight Tuning Framework			RecSys 2023	[Link]
	CR-SoRec: BERT driven Consistency Regularization for Social Recommendation			RecSys 2023	[Link]
	Leveraging Large Language Models for Sequential Recommendation			RecSys 2023	[Link]
	Beyond Labels: Leveraging Deep Learning and LLMs for Content Metadata			RecSys 2023	[Link]
GenRec	GenRec: Large Language Model for Generative Recommendation	LLaMA (7B)	LoRA	Arxiv 2023	[Link]
	Towards Personalized Cold-Start Recommendation with Prompts				[Link]
	Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations				[Link]
	Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations				[Link]
TIGER	Recommender Systems with Generative Retrieval			NIPS 2023	[Link]
	Better Generalization with Semantic IDs: A case study in Ranking for Recommendations			Arxiv 2023	[Link]
	Product Information Extraction using ChatGPT			Arxiv 2023	[Link]
	Enhancing Job Recommendation through LLM-based Generative Adversarial Networks			Arxiv 2023	[Link]
	Generative Job Recommendations with Large Language Model			Arxiv 2023	[Link]
	Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences			RecSys 2023	[Link]
	LLM-Rec: Personalized Recommendation via Prompting Large Language Models			Arxiv 2023	[Link]
	Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM			RecSys 2023	[Link]
	A Large Language Model Enhanced Conversational Recommender System			Arxiv 2023	[Link]
	LLaMA-E: Empowering E-commerce Authoring with Multi-Aspect Instruction Following			Arxiv 2023	[Link]
	The Unequal Opportunities of Large Language Models: Revealing Demographic Bias through Job Recommendations			EAAMO 2023	[Link]
	BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction			KDD 2023	[Link]
	A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems			Arxiv 2023	[Link]
	Knowledge Prompt-tuning for Sequential Recommendation			Arxiv 2023	[Link]
	Learning Supplementary NLP Features for CTR Prediction in Sponsored Search			KDD 2023	[Link]
	Leveraging Large Language Models for Pre-trained Recommender Systems			Arxiv 2023	[Link]
	Enhancing Recommender Systems with Large Language Model Reasoning Graphs			Arxiv 2023	[Link]
	Large Language Models as Zero-Shot Conversational Recommenders			CIKM 2023	[Link]
	RAH! RecSys-Assistant-Human: A Human-Central Recommendation Framework with Large Language Models			Arxiv 2023	[Link]
	TBIN: Modeling Long Textual Behavior Data for CTR Prediction			Arxiv 2023	[Link]
	LKPNR: LLM and KG for Personalized News Recommendation Framework			Arxiv 2023	[Link]
	LLMRec: Benchmarking Large Language Models on Recommendation Task			Arxiv 2023	[Link]
	ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation			Arxiv 2023	[Link]
	Prompt Distillation for Efficient LLM-based Recommendation			CIKM 2023	[Link]
	RecMind: Large Language Model Powered Agent For Recommendation			Arxiv 2023	[Link]
	Text Matching Improves Sequential Recommendation by Reducing Popularity Biases			CIKM 2023	[Link]
	Zero-Shot Recommendations with Pre-Trained Large Language Models for Multimodal Nudging			Arxiv 2023	[Link]
	Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations			Arxiv 2023	[Link]
	Evaluating ChatGPT as a Recommender System: A Rigorous Approach			Arxiv 2023	[Link]
	Unveiling Challenging Cases in Text-based Recommender Systems			RecSys Workshop 2023	[Link]
	Retrieval-augmented Recommender System: Enhancing Recommender Systems with Large Language Models			RecSys Doctoral Symposium 2023	[Link]
	User-Centric Conversational Recommendation: Adapting the Need of User with Large Language Models			RecSys Doctoral Symposium 2023	[Link]
	An Unified Search and Recommendation Foundation Model for Cold-Start Scenario			CIKM 2023	[Link]
	JobRecoGPT -- Explainable job recommendations using LLMs			Arxiv 2023	[Link]
	Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling			Arxiv 2023	[Link]
	Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation			Arxiv 2023	[Link]
	Lending Interaction Wings to Recommender Systems with Conversational Agents			NIPS 2023	[Link]
	A Multi-facet Paradigm to Bridge Large Language Model and Recommendation			Arxiv 2023	[Link]
	MuseChat: A Conversational Music Recommendation System for Videos			Arxiv 2023	[Link]
	EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce			Arxiv 2023	[Link]
	ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction			Arxiv 2023	[Link]
	AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems			Arxiv 2023	[Link]
	Factual and Personalized Recommendations using Language Models and Reinforcement Learning			Arxiv 2023	[Link]
	On Generative Agents in Recommendation			Arxiv 2023	[Link]
	Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation			Arxiv 2023	[Link]
	Collaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language Model			Arxiv 2023	[Link]
	A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models			Arxiv 2023	[Link]
	Language Models As Semantic Indexers			Arxiv 2023	[Link]
	Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language			Arxiv 2023	[Link]

2. Datasets & Benchmarks

The datasets & benchmarks for LLM-related RS topics should maintain the original semantic/textual features, instead of anonymous feature IDs.

2.1 Datasets

Dataset	RS Scenario	Link
Reddit-Movie	Conversational & Movie	[Link]
Amazon-M2	E-commerce	[Link]
MovieLens	Movie	[Link]
Amazon	E-commerce	[Link]
BookCrossing	Book	[Link]
GoodReads	Book	[Link]
Anime	Anime	[Link]
PixelRec	Short Video	[Link]

2.2 Benchmarks

Benchmarks	Webcite Link	Paper
Amazon-M2 (KDD Cup 2023)	[Link]	[Paper]
OpenP5	[Link]	[Paper]
TABLET	[Link]	[Paper]

3. Related Repositories

Repo Name	Maintainer
rs-llm-paper-list	wwliu555
awesome-recommend-system-pretraining-papers	archersama
LLM4Rec	WLiK
Awesome-LLM4RS-Papers	nancheng58
LLM4IR-Survey	RUC-NLPIR

Contributing

👍 Welcome to contribute to this repository.

If you have come across relevant resources or found some errors in this repesitory, feel free to open an issue or submit a pull request.

Contact: chiangel [DOT] ljh [AT] gmail [DOT] com

Citation

@article{lin2023can,
  title={How Can Recommender Systems Benefit from Large Language Models: A Survey},
  author={Lin, Jianghao and Dai, Xinyi and Xi, Yunjia and Liu, Weiwen and Chen, Bo and Li, Xiangyang and Zhu, Chenxu and Guo, Huifeng and Yu, Yong and Tang, Ruiming and others},
  journal={arXiv preprint arXiv:2306.05817},
  year={2023}
}

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